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Using Interaction for Simpler and Better Learning
Seminar Series: Machine Learning Seminar Series 2018
Speaker: Sanjoy Dasgupta
Host: Guy Bresler
Host Affiliation: MIT EECS
Date: Wednesday, April 18, 2018
Time: 3 PM
Location: 32-141 Stata Center
In the usual setup of supervised learning, the learner is given a
stack of labeled examples and told to fit a classifier to them.
It would be quite unnatural for a human to learn in this way, and
indeed this model is known to suffer from a variety of
fundamental hardness barriers. However, many of these hurdles can
be overcome by moving to a setup in which the learner interacts
with a human (or other information source) during the learning
We will see how interaction makes it possible to:
1. Learn DNF (disjunctive normal form) concepts.
2. Perform machine teaching in situations where the student’s
concept class is unknown.
3. Improve the results of unsupervised learning. We will present
a generic approach to “interactive structure learning” that, for
instance, yields simple interactive algorithms for topic modeling
and hierarchical clustering. Along the way, we will present a
novel cost function for hierarchical clustering, as well as an
efficient algorithm for approximately minimizing this cost.
Sanjoy Dasgupta is a Professor in the Department of Computer
Science and Engineering at UC San Diego. He works on algorithms
for machine learning, with a focus on unsupervised and
For more information please contact: Marcia G.
Davidson, 617-253-3049, firstname.lastname@example.org